AI Governance decision guide
Begin with one business outcome and a named owner.
The first useful AI conversation is usually not about deploying AI everywhere. It is about one business outcome, one workflow, the information it needs, the people affected, and the person accountable for deciding whether it should continue.
That approach gives an organization room to learn without leaving authority, access, and intervention unclear.
Six decisions before the use case expands
Define the purpose
Describe the outcome in plain language. Is the system helping prepare a draft, organize internal knowledge, support a service workflow, identify a question, or recommend a next action? A precise purpose makes limits easier to set and review.
Name the accountable owner
Identify the business sponsor who can approve the purpose, accept the use case's limits, decide when it changes, and stop it when the conditions no longer support it.
Set the information boundary
Decide which information may be used, which sources are excluded, what the system may retain or transmit, and what people must check before sharing an output. Public forms and unapproved systems are not appropriate places for sensitive material.
Define human authority
Specify whether a person is in the loop for a particular action, on the loop with defined oversight and intervention authority, or accountable for a final business decision. These are different operating roles. None transfers accountability to the system.
Test and record the work
Use representative scenarios, known limitations, error and escalation paths, logging, and review points that fit the consequence of being wrong. A test is useful only when it connects to the real context of use.
Establish change and stop conditions
Decide what must happen if the model, data, integration, users, purpose, risk, or performance changes. The appropriate response may be to reassess, constrain, pause, or retire the use case.
Use a framework to organize questions
NIST's voluntary AI Risk Management Framework offers four functions, Govern, Map, Measure, and Manage, that can help structure these discussions. The functions are not a certification or an ordered checklist. They are a way to make purpose, context, testing, and response visible.
eTrepid's role
Within an agreed scope, eTrepid can help structure the use case, clarify responsibilities and information boundaries, support integration and operating controls, and prepare a practical next-step plan. The client retains authority for its objectives, information, approvals, risk decisions, and business outcome. Where an engagement includes AIBOS, Auctoric owns the platform, intellectual property, licensing controls, core security architecture, and roadmap; eTrepid provides the separately contracted client-service scope.
Sources and limits
This candidate uses the current NIST AI RMF and Generative AI Profile as voluntary organizing guidance. NIST says AI RMF 1.0 is under revision. This is general information, not legal, compliance, certification, security, or regulated-decision advice.
Related: /ai-governance/ · /ai-as-a-system/ · /threatkrusher/command/